A Systematic Review of Bayesian Papers in Psychology: The Last 25 Years
Although the statistical tools most often used by researchers in the field of psychology over the last 25 years are based on frequentist statistics, it is often claimed that the alternative Bayesian approach to statistics is gaining in popularity.
The GRoLTS-Checklist: Guidelines for Reporting on Latent Trajectory Studies
Estimating models within the mixture model framework, like latent growth mixture modeling (LGMM) or latent class growth analysis (LCGA), involves making various decisions throughout the estimation process. This has led to a wide variety in how results of latent trajectory analysis are reported.
Wat zijn de regels van de wetenschap en liggen die voor altijd vast?
“Lang… lang geleden, in een dorp hier ver vandaan, stelden de eerste wetenschappers Vragen. Op een dag besloten zij dat Vragen stellen veel beter ging als ze zich terugtrokken uit het dorp en in een ivoren toren gingen werken. Daar konden zij in alle rust zoeken naar mogelijke antwoorden op de Vragen.
Measurement Invariance (book)
Multi-item surveys are frequently used to study scores on latent factors, like human values, attitudes and behavior. Such studies often include a comparison, between specific groups of individuals, either at one or multiple points in time.
Analyzing small data sets using Bayesian estimation: the case of posttraumatic stress symptoms following mechanical ventilation in burn survivors
The analysis of small data sets in longitudinal studies can lead to power issues and often suffers from biased parameter values. These issues can be solved by using Bayesian estimation in conjunction with informative prior distributions.
Latent Growth Mixture Models to estimate PTSD trajectories
Statistical models to estimate individual change over time and to investigate the existence of latent trajectories, where individuals belong to trajectories that are unobserved (latent), are becoming ever more popular.
A Gentle Introduction to Bayesian Analysis: Applications to Developmental Research
Bayesian statistical methods are becoming ever more popular in applied and fundamental research. In this study a gentle introduction to Bayesian analysis is provided. It is shown under what circumstances it is attractive to use Bayesian estimation, and how to interpret properly the results.
Bayesian analyses: where to start and what to report
Most researchers in the social and behavioral sciences will probably have heard of Bayesian statistics in which probability is defined differently compared to classical statistics (probability as the long-run frequency versus probability as the subjective experience of uncertainty).
Facing off with Scylla and Charybdis: a comparison of scalar, partial, and the novel possibility of approximate measurement invariance
Measurement invariance (MI) is a pre-requisite for comparing latent variable scores across groups. The current paper introduces the concept of approximate MI building on the work of Muthén and Asparouhov and their application of Bayesian Structural Equation Modeling (BSEM) in the software Mplus.
What Took Them So Long? Explaining PhD Delays among Doctoral Candidates
A delay in PhD completion, while likely undesirable for PhD candidates, can also be detrimental to universities if and when PhD delay leads to attrition/termination. Termination of the PhD trajectory can lead to individual stress, a loss of valuable time and resources invested in the candidate and can also mean a loss of competitive advantage.